MAAIG: Motion Analysis And Instruction Generation

2 Nov 2023 · Wei-Hsin Yeh, Pei Hsin Lin, Yu-An Su, Wen Hsiang Cheng, Lun-Wei Ku ·

Many people engage in self-directed sports training at home but lack the real-time guidance of professional coaches, making them susceptible to injuries or the development of incorrect habits. In this paper, we propose a novel application framework called MAAIG(Motion Analysis And Instruction Generation). It can generate embedding vectors for each frame based on user-provided sports action videos. These embedding vectors are associated with the 3D skeleton of each frame and are further input into a pretrained T5 model. Ultimately, our model utilizes this information to generate specific sports instructions. It has the capability to identify potential issues and provide real-time guidance in a manner akin to professional coaches, helping users improve their sports skills and avoid injuries.

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Adafactor • Attention Dropout • BPE • Dense Connections • Dropout • GELU • GLU • Inverse Square Root Schedule • Layer Normalization • Linear Layer • Multi-Head Attention • Residual Connection • Scaled Dot-Product Attention • SentencePiece • Softmax • T5

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MAAIG: Motion Analysis And Instruction Generation

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